2019/01/31 by Jason Hindes, Michael Assaf
Biochemistry, Genetics and Molecular Biology · Mathematics · Physics and Astronomy · Social Sciences · #Combinatorics #Complex Network Analysis Techniques #Complex network #Computer science #Constant (computer programming) #Degree (music) #Degree distribution #Demography #Dispersion (optics) #Evolutionary Game Theory and Cooperation #Exponential function #Extinction (optical mineralogy) #Mathematical analysis #Mathematics #Network topology #Opinion Dynamics and Social Influence #Physics #Population #Quantum mechanics #Rare events #Statistical physics #Statistics #Topology (electrical circuits) #Variance (accounting) #cond-mat.stat-mech #q-bio.PE
paper · pdf · doi:10.1103/physrevlett.123.068301
published as Phys. Rev. Lett. 123, 068301 (2019) · 5 pages, 4 figures + Supplemental Material. To appear in Phys. Rev. Lett. (2019)
arxiv created 2019/07/10 · openalex publication_date 2019/08/09 · arxiv updated 2019/08/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
There is great interest in predicting rare and extreme events in complex systems, and in particular, understanding the role of network topology in facilitating such events. In this Letter, we show that degree dispersion-the fact that the number of local connections in networks varies broadly-increases the probability of large, rare fluctuations in population networks generically. We perform explicit calculations for two canonical and distinct classes of rare events: network extinction and switching. When the distance to threshold is held constant, and hence stochastic effects are fairly compared among networks, we show that there is a universal, exponential increase in the rate of rare events proportional to the variance of a network's degree distribution over its mean squared.